The long term goal of this project is to develop novel algorithms and methods for improved prediction of RNA higher order structures, and for the rational and efficient design of antisense nucleic acids. Antisense oligonucleotides, trans-cleaving ribozymes and short interfering RNAs have emerged as increasingly important RNA-targeting tools for achieving efficient gene down-regulation. They are essential for high throughput functional studies of genes and gene products in humans, model organisms and infectious pathogens, as well as for the identification and validation of new therapeutic targets and agents against human diseases. To be effective, these antisense nucleic acid molecules require good target accessibility, which is primarily determined by the secondary structure of the target RNA. The secondary structures of mRNAs and viral RNAs are generally unknown, and are difficult to elucidate by experimental means. Therefore, computational methods could be valuable for the RNA structural determination. However, conventional RNA folding algorithms have not adequately addressed either the issue of uncertainty in the prediction or the issue of potential alternative structures for long-chain RNAs. Recently, a novel statistical sampling approach to RNA secondary structure prediction has presented a satisfying solution to these longstanding problems. This new method has been shown to offer important improvements for the prediction of messenger RNA structures and effective antisense targets, when compared to conventional methods. The objective of the present application is to develop algorithms and a methodology for the rational and efficient design of trans-cleaving ribozymes. This will be achieved by taking advantage of the statistical sampling method for target accessibility prediction and ribozyme design (Aim 1), by experimentally testing the computationally designed ribozymes both in vitro and in vivo, and to further improve the design methodology through statistical analysis and modeling of the experimental data (Aim 2). Finally, a software module incorporating the ribozyme design tools will be developed and made available to the scientific community through a Web server (Aim 3). Improved algorithms for RNA higher order structure prediction and more effective methods for the engineering of antisense nucleic acids are expected to result from this project. In the post-genomic era, the availability of the software and the Web server will substantially facilitate applications of antisense nucleic acids in high throughput functional genomics.